Principal Engineer, GKE Platform for AI Inference Workloads

Google Inc.; Seattle, Kirkland (WA, WA); On-site; USD 307,000 - 427,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with match

PTO 20 days per year

Sick time 40 hours/year (Seattle 69)

Job summary

Google Cloud's GKE Platform is seeking a Principal Engineer to reinvent AI inference workloads at scale. You will lead architectural reinvention for llm‑d, driving distributed infrastructure and high‑throughput networking across the GKE fleet.

Collaborate with DeepMind and Vertex AI to co‑define an AI‑first roadmap, leveraging Google's custom silicon to optimize throughput and density, while contributing to the CNCF OSS ecosystem.

Qualifications

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 15 years of experience in software engineering, or 15 years of experience with an advanced degree.
• Experience building distributed systems and driving technical strategy for platform-level infrastructure.
• Experience with Kubernetes, container runtimes, and AI/ML infrastructure (e.g., inference serving, LLM, hardware accelerators).

Responsibilities

• Lead the architectural direction for llm‑d, ensuring a highly optimized, scalable foundation for distributed LLM and RL serving across the GKE fleet.
• Define GKE's evolution to support massive‑scale inference and RL, solving orchestration problems in resource allocation and multi‑host scheduling.
• Partner with AI model builders to co‑develop an AI‑first roadmap and optimize throughput with custom silicon.
• Lead the broader Kubernetes OSS community, driving upstream initiatives to set standards for AI orchestration.

Skills

Kubernetes

Distributed systems

AI/ML infrastructure

High‑performance networking

Education

Bachelor's degree in Computer Science or related field

Master's degree or PhD in Computer Science or related field

Job description

Principal Engineer, GKE Platform for AI Inference Workloads

Share Principal Engineer, GKE Platform for AI Inference Workloads

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Seattle, WA, USA; Kirkland, WA, USA; Sunnyvale, CA, USA.

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 15 years of experience in software engineering, or 15 years of experience with an advanced degree.
• Experience building distributed systems and driving technical strategy for platform-level infrastructure.
• Experience with Kubernetes, container runtimes, and AI/ML infrastructure (e.g., inference serving, LLM, hardware accelerators).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• Experience interacting with senior customer stakeholders (CTOs, chief architects) to represent the technical vision of the organization.
• Demonstrated track record of significant technical contributions to the Kubernetes open-source project or related CNCF AI/ML projects (e.g., Kueue).
• Demonstrated track record of influencing cross-functional teams (product, engineering, research) to deliver complex technical outcomes.
• Deep technical understanding of high-performance networking (RDMA, NCCL), storage/caching architectures for massive model weights, and accelerator virtualization/sharing mechanisms.

About the job

Google Kubernetes Engine (GKE) is the industry standard for container orchestration and the core of Google Cloud’s modernization strategy. We are now embarking on a mission to reinvent GKE and Kubernetes as the premier substrate for the next generation of computing: AI inference at massive scale. We believe that serving foundation models and large language models represents a paradigm shift in cloud computing. These workloads demand a fundamental rethink of orchestration, moving from CPU-bound microservices to accelerator-bound, memory-bandwidth intensive workloads that require specialized scheduling, heterogeneous compute pools, and ultra-high-speed networking.

As the Principal Engineer, you will lead the technical and architectural reinvention of GKE to become the inference engine for the world. This leader will provide critical LLM Debugger (llm-d) leadership, defining and driving the long‑term strategic technical priorities for integrating high‑scale AI Inference and the llm‑d stack as a core competency into the GKE platform, while leading our contributions to the broader open‑source ecosystem.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise‑grade solutions that leverage Google’s cutting‑edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job‑related skills, experience, and relevant education or training.

US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits

• Lead the architectural direction for llm‑d , ensuring a highly optimized, scalable foundation for distributed LLM and Reinforcement Learning (RL) serving across the GKE fleet.
• Define GKE's evolution to support massive‑scale inference and RL, solving novel orchestration problems in dynamic resource allocation, multi‑host TPU/GPU scheduling, and high‑throughput networking.
• Partner with strategic AI model builders, DeepMind, and Vertex AI to co‑develop an AI‑first roadmap, leveraging Google's custom silicon to optimize throughput and compute density.
• Lead the broader Kubernetes ecosystem and Open Source Software (OSS) community, driving key upstream initiatives to establish industry standards for AI, RL, and accelerator orchestration.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.